The invention relates to a method for detecting image regions that are conspicuous in terms of the movement in them in a sequence of images of a scene; an apparatus, in particular for performing this method; and a corresponding computer program.
Video surveillance systems are used for monitoring such areas as streets, railroad stations, industrial plants, buildings, or squares with video cameras, and on the basis of the sequences of images recorded with the video cameras, discovering anomalies in the monitored areas.
While in earlier times the evaluation of the sequences of images was usually done by trained monitoring personnel, this monitoring activity is increasingly being either taken over or at least supported by computers. The computers use image processing algorithms for automatic evaluation of sequences of images. A typical principle for extracting moving objects from a monitored scene is to separate moving objects from the—essentially static—background of the scene, track them over time, and in the event of relevant patterns of motion, trip alarms. For object segmentation, particularly in the context of detecting the object in a sequence of image, the differences in the image between a current camera image and a so-called scene reference image that models the static background of the scene, are typically evaluated. Such image processing algorithms are described for instance in the scientific article by K. Toyama, J. Krumm, B. Brumitt, and B. Meyers: “Wallflower: Principles and Practice of Background Maintenance” in ICCV 1999, Corfu, Greece.
From other fields in image processing, namely video data compression, it is known to use what is known as the optical flow. For example, International Patent Disclosure WO 2005/006762 A2 defines the optical flow as the distribution of motion speeds of brightness patterns in an image, and uses the optical flow to improve the compression in video data streams. However, nothing about object detection or object tracking is found in this reference.